What to do with actionable intelligence: E2Coach as an intervention engine
What to do with actionable intelligence: E2Coach as an intervention engine
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如何利用可操作的情报：E2Coach 作为干预引擎
DOI：
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发表时间：
2012
期刊：
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通讯作者：
J. Tritz
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文献类型：
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作者：
T. McKay;Kate Miller;J. Tritz
在本文中，我们描述了一种新的，分析驱动的方法来支持学生在大型物理入门课程。在这个项目中，我们收集了密歇根大学49，000多名物理专业学生的数据。对于每一个，我们结合了联合收割机的背景和准备，通过课程和最终结果的进展细节广泛的画像。这些信息使我们能够构建模型，预测学生的表现与半个字母等级的分散。我们探索残差这个模型，进行结构化面试的学生做得比预期的更好（和更差），确定策略，导致学生的成功（和失败）在各级准备。这项工作是为了准备推出E2Coach：一个计算机定制的教育辅导项目，为干预引擎提供了一个模型，能够为数千名学生处理可操作的信息。
In this paper, we describe a new, analytics driven approach to supporting students in large introductory physics courses. For this project, we have assembled data for more than 49,000 physics students at the University of Michigan. For each, we combine an extensive portrait of background and preparation with details of progress through the course and final outcome. This information allows us to construct models predicting student performance with a dispersion of half a letter grade. We explore residuals to this model, conducting structured interviews with students who did better (and worse) than expected, identifying strategies which lead to student success (and failure) at all levels of preparation. This work was done in preparation for the launch of E2Coach: a computer tailored educational coaching project which provides a model for an intervention engine, capable of dealing with actionable information for thousands of students.